{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "toc": "true"
   },
   "source": [
    "# Table of Contents\n",
    " <p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "%config InlineBackend.figure_format='retina'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import GPflow\n",
    "import numpy as np\n",
    "\n",
    "nobsv=3000\n",
    "X = np.random.normal(size=(nobsv,2))\n",
    "Y = np.random.normal(size=(nobsv,1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 loop, best of 3: 5.23 s per loop\n"
     ]
    }
   ],
   "source": [
    "se = GPflow.kernels.RBF(2, lengthscales=1.0)\n",
    "gp = GPflow.gpr.GPR(X, Y, se)\n",
    "x=gp.get_free_state()\n",
    "gp._compile()\n",
    "gp._objective(x)\n",
    "%timeit gp._objective(x)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "python3 venv",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.1"
  },
  "nav_menu": {},
  "toc": {
   "navigate_menu": true,
   "number_sections": true,
   "sideBar": true,
   "threshold": 6,
   "toc_cell": true,
   "toc_section_display": "block",
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
